rm(list = ls(all.names = TRUE))
gc()
set.seed(211917)
options(scipen=999)

packages <-c("tidyverse","foreign","stargazer","naniar","xtable")

new.packages <- packages[!(packages %in% installed.packages()[,"Package"])]
if(length(new.packages)) install.packages(new.packages)

lapply(packages, require, character.only = TRUE)
rm(packages, new.packages)

setwd("PUT YOUR WORKING DIRECTORY HERE")

# load data
dat <- read.dta("./data.dta")

#---------------#
# Data cleaning #
#---------------#

# some preliminary cleaning
dat$q6_years_married[dat$q6_years_married == -9] <- 0
dat$treatment_binary <- ifelse(dat$holy_endorser==1 | dat$secular_endorser==1, 1, 0)

## select all possible covariates and outcome at first
dat <- dat %>% 
  select(q30_combined, treatment_binary, treatment, holy_endorser, secular_endorser, respondent_muslim, respondent_male, enumerator_muslim, enumerator_male, q1_age, q2_male, q3_kamba, q3_kikuyu, q3_luo, q3_somali, q3_other, q4_religion_christian, q4_religion_muslim, q5_convert, q6_years_married, q6_married, q7_has_job, q8_income_last_month, q8_has_income, q9_chance_become_rich, q10_plans_to_vote, q11_govt_represents_interest, q12_feels_on_loosing_side, q13_a_knows_emigrant, q13_b_knows_emigrant_som_eri, q15_witnesses_interrel_violence, q16_witnesses_viol_musl_govt, q17_friend_family_died, q18_lost_job, q18_arrested, q18_house_of_worship_raided, q18_stopped_speaking_parents, q18_love_problems, q18_friend_left_country, q18_sum, q19_rlts_mother, q19_not_raised_by_mom, q19_mother_dead, q20_rlts_father, q20_not_raised_by_father, q20_father_dead, q21_respect_friends_family, q22_gender, q22_religion, q22_tribal, q22_national, q22_youth, q23_religious_attendance, q23_frequents_house_worship, q24_deontology, q25_payment_acceptable, q26_payment_ethical, q27_radicalization, q33_distance)

## check for missings
vis_miss(dat)

## following variables seems problematic, i.e., shouldn't impute at this level
table(is.na(dat$q13_a_knows_emigrant))
table(is.na(dat$q19_rlts_mother))
table(is.na(dat$q20_rlts_father))
table(is.na(dat$q23_religious_attendance))

## kick problematic vars out
dat <- dat %>% select(-q13_a_knows_emigrant, -q19_rlts_mother, -q20_rlts_father, -q23_religious_attendance)

## check missing again:
vis_miss(dat) 

## remove one missing treatment indicator (can't be imputed)
dat <- dat[which(dat$holy_endorser>-1),]

## impute rest of missings with mean 
for(i in 1:ncol(dat)){
  dat[is.na(dat[,i]), i] <- mean(dat[,i], na.rm = TRUE)
}
rm(i)

## to be save, remove missing cases
dat <- dat[complete.cases(dat), ]

dat$q30_combined_s <- scale(dat$q30_combined)

killing_d <- dat[which(dat$treatment==1),]
suicide_d <- dat[which(dat$treatment==2),]

## rename treatment such that 1 means suicide
dat$treatment <- dat$treatment-1

#----------------------#
# OLS without controls #
#----------------------#

# interaction
lm_interaction_wo_controls <- lm(q30_combined_s ~ treatment_binary*treatment*respondent_muslim, data=dat)
summary(lm_interaction_wo_controls)

#-------------------#
# OLS with controls #
#-------------------#

## extract all possible controls
controls <- as.character(colnames(dat[,6:55]))

## drop enumerator FEs for now, add later
controls <- controls[c(1:2, 5:50)]

lm_interaction_all_controls <- lm(paste("q30_combined_s ~ treatment_binary*treatment*respondent_muslim + ", paste(controls, collapse=" + ")), data = dat)


#-------------------------------------#
# OLS with controls and Fixed Effects #
#-------------------------------------#

# set seed
set.seed(12345)

## extract all possible controls
controls <- as.character(colnames(dat[,6:55]))

lm_interaction_all_controls_fes <- lm(paste("q30_combined_s ~ treatment_binary*treatment*respondent_muslim + ", paste(controls, collapse=" + ")), data = dat)


stargazer(lm_interaction_wo_controls, lm_interaction_all_controls, lm_interaction_all_controls_fes,
          omit = c("Constant", "respondent_male", "enumerator_muslim", "enumerator_male", "q1_age", "q2_male", "q3_kamba", "q3_kikuyu", "q3_luo", "q3_somali", "q3_other", "q4_religion_christian", "q4_religion_muslim", "q5_convert", "q6_years_married", "q6_married", "q7_has_job", "q8_income_last_month", "q8_has_income", "q9_chance_become_rich", "q10_plans_to_vote", "q11_govt_represents_interest", "q12_feels_on_loosing_side", "q13_a_knows_emigrant", "q13_b_knows_emigrant_som_eri", "q15_witnesses_interrel_violence", "q16_witnesses_viol_musl_govt", "q17_friend_family_died", "q18_lost_job", "q18_arrested", "q18_house_of_worship_raided", "q18_stopped_speaking_parents", "q18_love_problems", "q18_friend_left_country", "q18_sum", "q19_rlts_mother", "q19_not_raised_by_mom", "q19_mother_dead", "q20_rlts_father", "q20_not_raised_by_father", "q20_father_dead", "q21_respect_friends_family", "q22_gender", "q22_religion", "q22_tribal", "q22_national", "q22_youth", "q23_religious_attendance", "q23_frequents_house_worship", "q24_deontology", "q25_payment_acceptable", "q26_payment_ethical", "q27_radicalization", "q33_distance"),
          covariate.labels = c("Treatment"),
          add.lines = list(c("Controls", "No", "Yes", "Yes"),
                           c("FEs", "No", "No", "Yes")),
          keep.stat = c("n", "adj.rsq"),
          digits = 3,
          dep.var.caption = "",
          dep.var.labels = "",
          label = "tab:main",
          title = "Effect of religious primes on attitudes toward violence",
          out = "PUT YOUR FILE PATH HERE")



